Machine learning for email spam filtering: review, approaches and open research problems

The upsurge in the volume of unwanted emails called spam has created an intense need for the development of more dependable and robust antispam filters. Machine learning methods of recent are being used to successfully detect and filter spam emails. We present a systematic review of some of the popu...

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Bibliographic Details
Published in:	Heliyon Vol. 5; no. 6; p. e01802
Main Authors:	Dada, Emmanuel Gbenga, Bassi, Joseph Stephen, Chiroma, Haruna, Abdulhamid, Shafi'i Muhammad, Adetunmbi, Adebayo Olusola, Ajibuwa, Opeyemi Emmanuel
Format:	Journal Article
Language:	English
Published:	England Elsevier Ltd 01.06.2019 Elsevier
Subjects:	Analysis of algorithms Computer privacy Computer science Computer security Deep learning e-mail Internet Machine learning Naïve Bayes Neural networks Spam filtering Support vector machines surveys systematic review Computer science Deep learning Support vector machines Naïve Bayes Spam filtering Neural networks Machine learning Analysis of algorithms Computer security Computer privacy
ISSN:	2405-8440, 2405-8440
Online Access:	Get full text
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